Table 2.
Cross-validation | 10 | 20 | 50 | 100 | 200 | 400 | 800 | 1200 | 2000 | 3000 | 4000 | All (5081) |
---|---|---|---|---|---|---|---|---|---|---|---|---|
2 Sample t-test | 0.64 | 0.67 | 0.63 | 0.58 | 0.62 | 0.69 | 0.71 | 0.72 | 0.74 | 0.76 | 0.77 | 0.77 |
Nested CV | 0.62 | 0.64 | 0.65 | 0.63 | 0.62 | 0.64 | 0.68 | 0.70 | 0.75 | 0.77 | 0.76 | 0.77 |
Recursive FE | 0.64 | 0.63 | 0.63 | 0.67 | 0.69 | 0.72 | 0.74 | 0.76 | 0.77 | 0.77 | 0.77 | 0.77 |
Test set | 10 | 20 | 50 | 100 | 200 | 400 | 800 | 1200 | 2000 | 3000 | 4000 | All (5081) |
2 Sample t-test | 0.74 | 0.76 | 0.73 | 0.69 | 0.61 | 0.61 | 0.68 | 0.70 | 0.70 | 0.72 | 0.74 | 0.74 |
Nested CV | 0.67 | 0.70 | 0.74 | 0.67 | 0.59 | 0.70 | 0.71 | 0.70 | 0.71 | 0.71 | 0.73 | 0.74 |
Recursive FE | 0.68 | 0.63 | 0.52 | 0.54 | 0.63 | 0.71 | 0.74 | 0.75 | 0.75 | 0.74 | 0.74 | 0.74 |
Results summarizing ADHD prediction using anatomical features only. Entries indicate the area under the ROC curve (AUC) for classifiers built using different feature selection methods (rows) and different numbers of features (columns). Top: results on leave-out folds during cross-validation. Bottom: results on separate test set based on training across all examples in the training/cross-validation set.